Large Area Coverage Research Articles

The role of the state in the financing sources’ formation of industrial enterprises’ innovative activities

Currently, the external conditions for the functioning of industrial enterprises are formed in such a way that the achievement of their goals is seen impossible without the implementation of innovative activities. Due to the high cost of innovations, as well as the need to conduct these processes on an ongoing basis, industrial enterprises lack their own funds to finance innovation activities. The state is interested in the innovative development of industrial enterprises. This is one of the reasons why it participates in the formation of their funding sources. The article substantiates the need for state support, as well as analyzes the options for its provision by type of financing sources. For each type of sources, options for providing large-scale support, implying a large coverage area, as well as point-directed support, are also highlighted.

A Direction-Sensitive Microwave Sensor for Metal Crack Detection

For metal crack nondestructive detection, most conventional crack sensors are unable to realize the crack direction detection. In this work, a direction-sensitive microwave sensor is proposed for metal crack detection. The proposed sensor consists of a rectangular patch resonator and two perpendicular coupled feeding ports, which improves the current distribution on patch surface and the sensitivity for crack direction detection. The performances of the proposed sensor are verified by simulation and measurement experiments. The results show that the width sensitivities of two feeding ports are 100 MHz/mm and 63.3 MHz/mm, respectively, and the sensitivity of the sensor for crack direction detection are 6.10 MHz/5 degrees and 1.93 MHz/5 degrees, respectively. Due to the advantages of a simple structure, low profile, large coverage area and high sensitivity, the proposed sensor has a great application potential in nondestructive detection fields.

I2M: Intelligent Information Management for Rendering IoE Services in Society 5.0

In this paper, we propose an intelligent information management scheme – I2M – an two level delay-tolerant profile matching scheme for provisioning Internet-of-Everything (IoE) services in a Society 5.0. The primary aim of Society 5.0 is to provide seamless real-time IoE services using artificial intelligence (AI) and next-generation networks (NGNs). In this context, we introduce Information-Centric Satellite Network (ICSN), which is expected to enable efficient in-network caching, content delivery, and large area coverage in Society 5.0. The existing works on ICSNs suggest caching the information, requested by the user, in the satellites. However, the satellites are storage-constraint in nature. Therefore, storing information in such satellites, in the long run, may not be a suitable solution. Moreover, the existing solutions increase the delay while a cache-miss occurs in ICSN, which is unacceptable in providing real-time IoE services in Society 5.0. On the other hand, data requested by the increased number of users results in reduced network lifetime and transmission efficiency for Society 5.0 without having a suitable load balancing mechanism in the existing ICSN. To address these issues, we design I2M, which is capable of managing information in a Society 5.0. In I2M, we introduce a tabular data structure to store, update, and replace in-network information in the resource-constrained satellites. Using this tabular data structure, I2M performs a 2-level profile matching scheme, which helps to efficiently access the in-network information and reduce the delay for cache-miss in satellites. Additionally, to increase the transmission efficiency and network lifetime, we apply a long-shot term memory (LSTM)-based intelligent load balancing mechanism in I2M. The extensive simulation results show that I2M outperforms as compared to the existing schemes for ICSNs, in terms of energy consumption, packet loss, and delay. We observe that I2M is capable of reducing delay by 35-55%, energy consumption by 34-54%, and packet loss by 36-53%.

Geological Hazards in Al-Anbar Governorate, West Iraq

Al-Anbar Governorate has the largest coverage area among the 18 Iraqi gover-norates. The coverage area is about 138 579 km2 forming about 32% of the whole coverage area of the Iraqi territory. The governorate forms the western part of Iraq representing the Iraqi Western Desert and a small part north of the Eu-phrates River within the Jazira Plain. This large coverage area with diversity of rock types with large time span (Permi-an – Pleistocene) and different topographic forms have contributed to develop-ment of different types of geological hazards, which act at different parts of the governorate with different intensities and different damages caused to the infra-structure and community, even life losses. Three main types of geological hazards are active in the governorate; these are: 1) Floods, 2) Karstification, and 3) Swell-ing (Expensive) clays; however, other types like mass movements, depressions, active tectonic areas are also present but with less significance as their risks and caused damages to the community and infrastructure is concerned.

Enhancement of valley polarization in CVD grown monolayer MoS2 films

The development of future valley based electronics or valleytronics requires a high degree of valley polarization (VP) in large area monolayer (1L)-MoS2. Though it is possible to synthesize 1L-MoS2 films with large area coverage, VP property of as-grown films is found to be very poor. Here, we investigate the role of physisorbed air molecules and strain on the luminescence and the VP characteristics of large area monolayer MoS2 grown on various substrates by a microcavity based chemical vapor deposition (CVD) technique. The study shows that the removal of adsorbates from sulfur vacancy (VS) sites not only suppresses the broad sub-bandgap luminescence feature that typically dominates low temperature photoluminescence (PL) spectra of these films but also significantly enhances VP. Post-growth transfer of the 1L-MoS2 film from sapphire to a SiO2/Si substrate by a polystyrene assisted process is found to be highly effective in improving the polarization characteristic (∼80%) of K-valleys through relaxation of the biaxial tensile strain and the removal of physisorbed air molecules from the VS sites. The process is also found to provide long lasting protection for MoS2 films from air. The finding, thus, creates much needed opportunity to use CVD grown large area 1L-MoS2 for realization of valleytronics of the future.

Vegetation indices as a Tool for Mapping Sugarcane Management Zones

In precision agriculture, the adoption of management zones (MZs) is one of the most effective strategies for increasing agricultural efficiency. Currently, MZs in sugarcane production areas are classified based on conventional soil sampling, which demands a lot of time, labor and financial resources. Remote sensing (RS) combined with vegetation indices (VIs) is a promising alternative to support the traditional classification method, especially because it does not require physical access to the areas of interest, is cost-effective and less labor-intensive, and allows fast and easy coverage of large areas. The objective of this study was to evaluate the ability of the normalized difference vegetation index (NDVI) and the two-band enhanced vegetation index (EVI2) to classify sugarcane MZs, compared with the conventional method, in the Brazilian Cerrado biome (savannah), where about half of Brazil´s sugarcane production takes place. This study used historical crop production data from 5,500 production fields in three agricultural years (2015 to 2018) and NDVI and EVI2 values of 14 images acquired by the Landsat 8 satellite from 2015 to 2018 in Google Earth Engine (GEE). Although improvements are still necessary and encouraged, a new methodology of classifying MZs according to VIs was proposed in this study. The NDVI was not correlated with MZs classified using the conventional method, whereas EVI2 was more sensitive to biomass variations between MZs and, therefore, could better discriminate between MZs. The EVI2 values measured in crops aged 180 to 240 days in the rainy season proved to be the best strategy for classifying MZs by RS, where MZ A, for example, had EVI2 of 0.37, compared to MZ E, which had an EVI2 of 0.32.

Multidimensional soil salinity data mining and evaluation from different satellites

Soil salinization, a common land degradation mode, restricts the ecological environment and is a global issue due to climate change. Accurately, quickly and effectively monitoring soil salinity is critical for governmental institutions that develop hazard prevention and mitigation strategies. Remote sensing (RS) technology provides a viable alternative to traditional field work due to its large area coverage, abundant spectral information and nearly constant observations. Key issues in RS-based soil salinity monitoring include the lack of both data-mining techniques for obtaining spectral band information and comprehensive considerations of synergies among different spectra. The main objective of this study was to provide in-depth explorations of data mining and integration algorithms from different satellites to multidimensionally evaluate soil salinity models. The Ebinur Lake Wetland Reserve (Xinjiang Province, China) was selected as a case study. First, ground-measured visible and near infrared (VIS-NIR) spectral data were combined with the RS band to simulate Landsat 8 (L8) and Sentinel 2 (S2) and 3 (S3) data. Second, one-dimensional RS bands and 15 soil salinity and vegetation indices were selected, and 15 spectral data transformations (reciprocal, differential, absorbance, etc.) were obtained. Two- and three-dimensional spectral indices were constructed, and the response relationships between different spectral indices and soil electrical conductivity (EC) were comprehensively explored. Finally, an integrated multidimensional algorithm was used to estimate soil salinity in high-performance models for the three satellites. The results showed that all data-mining-based model combinations performed well for all satellites (R2 > 0.80). However, with multidimensional model combinations, S3 presented the highest predictive capability (R2 = 0.89, RMSE = 2.57 mS·cm−1, RPD = 2.05), followed by S2 (R2 = 0.86, RMSE = 2.71 mS·cm−1, RPD = 1.90) and L8 (R2 = 0.85, RMSE = 2.84 mS·cm−1, RPD = 1.87). Therefore, data mining with integration algorithms in model combinations performs significantly better than previous models and could be considered a promising method for obtaining improved results from soil salinity susceptibility models in similar cases.

Extensive Evaluation of Four Satellite Precipitation Products and Their Hydrologic Applications over the Yarlung Zangbo River

Satellite remote sensing precipitation products with high temporal–spatial resolution and large area coverage have great potential in hydrometeorological research. This paper analyzes the performance of four satellite products from 2000 to 2008 in the Yarlung Zangbo River Basin, namely the Tropical Rainfall Measuring Mission (TRMM), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Climate Prediction Center morphing method (CMORPH). The four products are evaluated from three aspects: spatial distribution, temporal characteristics, and hydrological simulation. The results show that: (1) the four products exhibit similar annual and daily precipitation patterns, with the highest daily precipitation accuracy concentrated in the center, followed by the east and west; (2) TRMM, CHIRPS, and CMORPH exhibit the largest positive bias for monthly precipitation estimation in December, while PERSIANN shows the largest positive bias in July. All products overestimate the precipitation of 0.1–5 mm/d, and underestimate the precipitation above 5 mm/d, especially for PERSIANN; (3) certain Products tend to perform better than others at elevations of 3000–4000 m and in relatively humid zones. TRMM shows relatively stable performance for various elevation and climate zones; (4) for hydrological model validation, TRMM has the best performance during the calibration period, although it is inferior to CHIRPS during the validation period. Overall, TRMM has the highest applicability in the Yarlung Zangbo River Basin; however, its impact on the uncertainty of hydrological modeling needs to be further studied.

Mixing processes in a reservoir corresponding to different water level operations caused spatial differences during two phytoplankton bloom events

Reservoir operation may impact algal blooms by altering flow conditions, but relevant studies and a theoretical understanding of this subject are limited. In this study, two phytoplankton bloom events with different spatial coverage patterns in a reservoir were investigated. By examining environmental variables, a suitable nutrient content and water temperature were considered responsible for bloom initiation during both events, but the different water level operations could possibly explain the observed spatial difference. A two-dimensional hydrodynamic numerical model was then used to simulate the mixing processes within the reservoir during these two bloom events. The simulation results indicated that the rising water level during the bloom event with a larger coverage area caused closed circulation flow conditions above the intrusion layer, displacing surface water in front of the dam upstream until reaching inflowing river water, which then intruded to support water offtake and water level lifting operations, while the other event did not exhibit a similar flow pattern. The water age was sensitive to water level operation, which suggested that phytoplankton dispersal could be promoted by rising water level processes. Inflow densimetric Froude number analysis indicated that reservoir impoundment facilitated a conversion of the inflow kinetic energy into potential energy, thus promoting algal dispersal via circulation. This study provides insights into the impact of reservoir operation on phytoplankton communities, offering a reference for operational design to mitigate algal blooms in reservoirs.

Exploring Maritime Search and Rescue Resource Allocation via an Enhanced Particle Swarm Optimization Method

Maritime search and rescue (SAR) plays a very important role in emergency waterway traffic situations, which is supposed to trigger severe personal casualties and property loss in maritime traffic accidents. The study aims to exploit an optimal allocation strategy with limited SAR resources deployed at navigation-constrained coastal islands. The study formulates the problem of SAR resource allocation in coastal areas into a non-linear optimization model. We explore the optimal solution for the SAR resource allocation problem under constraints of different ship and aircraft base station settings with the help of an enhanced particle swarm optimization (EPSO) model. Experimental results suggest that the proposed EPSO model can reasonably allocate the maritime rescue resources with a large coverage area and low time cost. The particle swarm optimization and genetic algorithm are further implemented for the purpose of model performance comparison. The research findings can help maritime traffic regulation departments to make more reasonable decisions for establishing SAR base stations.

Deep learning-based investigation of the impact of urban form on the particulate matter concentration on a neighborhood scale

Despite the importance of urban forms to the dispersion of particulate matter (PM), only a few studies exist on the relationship between them due to the limitations of the data and methodology. Thus, this study used a deep learning-based investigation of the impact of urban form on PM2.5 concentration. Autoencoder, long short-term memory (LSTM), and the random forest model were used to analyze their relationship. The random forest model showed that urban form variables predict PM2.5 concentration with a 95.66% accuracy, confirming that urban form characteristics significantly impact PM2.5 concentrations. Among the urban form variables, floor area ratio turned out to be the most important, suggesting the need for more detailed efforts to reduce PM2.5 in locations with high floor areas. The effect on PM2.5 prediction accuracy was evaluated with root mean square error. It was difficult to accurately predict PM2.5 in areas with large building coverage areas and low-rise residential areas. This study improved the accuracy of results on the influence of urban form by using PM2.5 non-aggregated data measured hourly over 4 years, which expanded the applicability of deep learning-based urban analysis.

Industrial waste-based submicron additives in cement mortars

Purpose: The aim of this work is the development of materials and technologies, which provide their repeated life cycle. Methodology/approach: Scanning electron microscopy, thermogravimetric analysis, X-ray diffraction analysis. Research findings: The processing method is proposed for fluorocarbon-containing waste (RUSAL, Krasnoyarsk) resulting in the formation of submicron-sized carbon in the form of a coal-water slurry for solution and/or concrete modification. It is shown that carbon in the coal-water slurry represents flat plates with the submicron-sized particles. The degree of cement hydration increases with the addition of wastes, indicating the material strengthening, which is consistent with the results of strength tests. The acicular spike crystals of hydrated calcium silicates become larger and thicker, that confirms the assumption that hydration increases with the addition of submicron-sized carbon particles. Practical implications: The obtained physical and mechanical properties of the cement-sand mortar show the possibility of using the proposed modifiers in the production of materials with high bending strength at early stages to reduce cracking, especially in thin concrete layers with a large coverage area.

Application of pre-positioning method in compressor cascade measurement with pressure-sensitive paint

The pressure-sensitive paint (PSP) technique has shown superiorities in its large coverage area capability and high spatial resolution. The process of the PSP technique usually requires sufficient illumination that covers the entire test object, and a camera that acquires the particular excited fluorescence. Applications in internal flow study, like the compressor cascade, may fail as the optical access is heavily limited due to the closely adjacent components, which creates a high demand for spatial positioning arrangement of optical devices in the visualization system. In this work, a pre-positioning method was proposed to help determine the arrangement of optical devices of an internal flow PSP measurement system in advance. It was applied to the measurement of a linear compressor cascade with large solidity. The results showed that with the optical layout arrangement determined using this pre-positioning method, a full-field pressure distribution of the cascade blade can be acquired successfully.

Flow field investigation of a straight–swirling integrated jet for radial jet drilling

Radial jet drilling (RJD) technology is applied to low permeability oil-gas reservoirs, coalbed methane, and shale gas. A self-propelled bit is an integral component. The external flow fields of a new-type of straight–swirling integrated jet (SSIJ) were tested under non-submerged conditions and the key parameters of the jet were studied in this paper. A rock-breaking experiment at a specific target distance was conducted to verify the PIV test results. It is indicated that, from the introduction of a central straight jet, the central low-axial-velocity zone can be eliminated, and the maximum radial and tangential velocities are not at the jet axis. Second, the hydraulic parameters do not affect the velocity distribution law, but significantly affected by nozzle structures. The straight-to-swirl ratio and the dip-angle of an impeller slot should be 0.8 and 45°, respectively, to obtain a flow field with both a higher central velocity and larger coverage area. Through the rock-breaking experiment, it was found that when the dip-angle is 45° (swirl number of 0.45), both the borehole depth and diameter are larger, and the bottom is the flattest, simultaneously, the correctness of the PIV test is verified. Finally, since the two jets (straight & swirling) have interacted and mixed after ejected from the nozzle, there is no constant velocity core, the SSIJ has no initial and basic sections compared with the conventional combined jet, and could be divided into a transition section and uniform-mixing section along the axial. By analyzing the swirl numbers at different positions, it was found that the SSIJ has a straight, weak-swirl, strong-swirl, and periphery jet zones along the radial. The results can guide rock-breaking mechanism revelation and the optimal design of an SSIJ bit for the RJD technology.

Scalable Thousand Channel Penetrating Microneedle Arrays on Flex for Multimodal and Large Area Coverage BrainMachine Interfaces (Adv. Funct. Mater. 25/2022)

Microneedle Arrays In article number 2112045, Shadi A. Dayeh and co-workers have invented an advanced brain–computer interface with a flexible and moldable backing and penetrating microneedles, which are 10 times thinner than the human hair. The flexible backing allows the device to more evenly conform to the brain's complex curved surface and to more uniformly distribute the microneedles that pierce the cortex without piercing surface venules and to record signals from nearby nerve cells evenly across a wide area of the cortex.

Effect of manganese incorporation on the excitonic recombination dynamics in monolayer MoS2

Using x-ray photoelectron spectroscopy, atomic force microscopy, and Raman spectroscopy techniques, we investigate the incorporation of manganese (Mn) in monolayer (1L)-MoS2 grown on sapphire substrates by microcavity based chemical vapor deposition method. These layers are coated with different amounts of Mn by pulsed laser deposition technique. The study reveals two contrasting Mn-incorporation regimes. Below a threshold deposition amount, thin Mn-coating with large area coverage is found on MoS2 layers where substitution of Mo ions by Mn is detected through XPS. Dewetting takes place when Mn deposition crosses the critical mark, resulting in the formation of Mn-droplets on MoS2 layers. In this regime, substitutional incorporation of Mn is suppressed, while the Raman study suggests an enhancement of disorder in the lattice with the Mn deposition time. This knowledge can help us in tackling the challenge of doping of 2D transition metal dichalcogenides in general. From the temperature dependent photoluminescence study, it has been found that, even though Mn deposition enhances the density of non-radiative recombination channels for the excitons, the thermal barrier height for such recombinations to take place also rises. The study attributes these non-radiative transitions to Mo-related defects (Mo-vacancies and/or distorted Mo–S bonds), which are believed to be generated in large numbers during Mn-droplet formation stage.

An internet of radiation sensor system (IoRSS) to detect radioactive sources out of regulatory control

A radioactive source that is not under regulatory control, either because it has never been under regulatory control or because it has been abandoned, lost, misplaced, stolen, or otherwise transferred without proper authorization, is considered an orphan source. Orphan sources are usually gathered as scrap metal because of their heavy metallic containers. Melting an orphan source with scrap metal produces contaminated recycled metal and waste; the consequences will be extremely serious for humans and the environment, affecting the economy and social stability. In this paper, we propose and develop an Internet of Radiation Sensor System (IoRSS) to detect radioactive sources out of regulatory control in scrap metal recycling and production facilities. It is a complete IoT system consisting of a network of wirelessly connected radiometric devices that optimizes the detection, localization, and identification of radioactive sources by integrating data from multiple portable radiation detectors. The proposed IoRSS system creates a robust and flexible network architecture along with advanced data fusion algorithms that combine information from many detectors. The IoRSS system provides advanced search and monitoring capabilities in a large coverage area and in difficult operational environments.

Discrete, Shallow Doping of Semiconductors via Cylinder‐Forming Block Copolymer Self‐Assembly

AbstractBlock copolymer (BCP) self‐assembly‐assisted doping for semiconductors is used to achieve discrete doping with nanometer‐scale junction depth, high throughput, and large area coverage. As devices become smaller and more sophisticated, spatial control of dopants becomes more critical. A variety of doping methods, such as monolayer doping and δ‐doping, have been developed to replace the conventional doping method, ion‐implantation; however, lateral patterning of dopants relies on photo‐ or e‐beam lithography. To address these challenges, a self‐assembling dopant (boron)‐containing BCP is designed to directly pattern dopants on the nanometer scale. This method skips the lithography step and is compatible with directed self‐assembly approaches. The effect of the boron concentration in the BCP on the doping performance is systematically studied by changing the volume fraction of the boron‐containing block while keeping the domain spacing and the mesoscale morphology constant. Successful self‐assembly of the BCP into a hexagonally packed cylindrical morphology is confirmed by small‐angle X‐ray scattering and resonant soft X‐ray scattering with a 26 nm cylinder‐to‐cylinder distance. Doping silicon using these BCPs enables discrete doped areas with shallow (7–13 nm) junction depth as demonstrated by the depth profile of boron, and supported by a sheet resistance study.

Magnetized supersonic downflows in the chromosphere

The chromosphere above active regions (ARs) on the Sun hosts magnetized supersonic downflows. Studies of these supersonic downflows help to decipher the magnetic fine structure and dynamics of the chromosphere. We perform a statistical analysis of the magnetized supersonic downflows in a number of ARs at different evolutionary stages and survey their characteristics. We analyze spectro-polarimetric scans of parts of 13 ARs obtained in the infrared He I 10 830 Å triplet formed in the upper chromosphere recorded with the GREGOR Infrared Spectrograph mounted at the GREGOR solar telescope. We retrieve the line-of-sight velocities and the magnetic field vector using the HELIX+ inversion code that assumes Milne-Eddington atmospheres. We find magnetized supersonic downflows in all the ARs, with larger area coverage by such flows in ARs observed during their emerging phase. The fact that supersonic downflows were detected in all scans, albeit only covering a small fraction, 0.2–6.4%, of the observed field-of-view, suggests that they are a comparatively common phenomenon in the upper chromospheres of ARs. The supersonic downflows are found to be associated with many AR features, such as pores, sunspot umbrae, sunspot penumbrae, light bridges, plages, He I loops as part of arch filament systems characteristic of emerging fields, and filaments. Although several mechanisms are identified to be causing the supersonic downflows, by far the most common one appears to be the draining of plasma along the legs of rising magnetic loops. The loops mainly drain into forming pores. The line-of-sight velocities of the supersonic downflows reach values of up to 49 km s−1, and the velocity distribution shows multiple populations. Almost 92% of these supersonic downflows coexist with a subsonic flow component. The weaker, more horizontal fields associated with the supersonic component suggests that it is formed above the subsonic component.

Improving time and position resolutions of RPC detectors using time over threshold information

INO-ICAL is a proposed underground experiment to study the oscillation parameters of neutrinos by detecting those produced in the atmospheric air showers. The Iron CALorimeter (ICAL) is to have 151 layers of iron plates stacked vertically corresponding to a height of ∼14.5 m, with active detector elements inserted between the iron layers. The iron layers will be magnetized with a maximum magnetic field of 1.5 T to enable the measurement of the charge and momentum of the μ - (or μ +) produced by ν μ (or ν̅ μ ) interactions inside the detector throughout the operation. Resistive Plate Chambers (RPCs) have been chosen as the active detector elements as they are amenable to large area coverage, as well as due to their high particle detection efficiency, long-term performance and low cost of production. The major factors that weigh in on the physics potential of the ICAL detector are the efficiency, position resolution and time resolution of the large area RPCs. A prototype detector called mini-ICAL (with 11 iron layers) was commissioned in order to understand the engineering challenges in building the large-scale electromagnet and its ancillary systems, and also to study the performance of the RPC detectors and readout electronics developed by the INO collaboration. As part of the performance study of the RPC detectors, an attempt is made to improve their position and time resolutions. The designed position resolution for the ICAL detector is of the order of 1 cm and the required time resolution is ∼1 ns. Even a small improvement in the position and time resolution will help to improve the measurements of momentum and directionality of the neutrinos in the ICAL detector. In ICAL detector simulation, where muons traverse in all directions with on average 20 RPC layers, a 30 % improvement in position resolution results in ∼10 % improvement in the momentum resolution at 3 GeV. Due to large iron materials in between two RPCs, the resolution is dominated by the effect of multiple scattering at this momentum. Also for a muon with 10 layer hit, the charge ambiguity reduces from 0.04 % to 0.001 % when the time resolution improves from 1 ns to 0.7 ns. The Time-over-Threshold (ToT) of the RPC pulses is recorded by the readout electronics. ToT is a measure of the pulse width and consequently the pulse amplitude. This information is used to improve the time and position resolution of RPCs and consequently INO's physics potential.